Obesity has been a well-recognized serious health problem in the United States for decades, significantly contributing to shortening lives and increasing medical expenses for millions of Americans. Many diseases, such as type II diabetes, hypertension, hyperlipidemia, heart disease, and others have been directly linked to obesity. Unfortunately, the threat of a reduced lifespan, reduced quality of life and an enhanced probability of suffering from comorbid diseases in the future is not sufficient for those who are significantly overweight to be successful in reducing their weight and in maintaining such a reduced weight, and a healthy lifestyle incorporating a consistent exercise program.
The causes of obesity are multiple and can be complex. Genetic predisposition impacting metabolism and environmental factors such as diminished physical activity often play a key role. For some individuals additional psychological factors such as stress and depression and medical conditions such as hypothyroidism, chronic pain and other conditions that restrict physical activity or affect metabolism all can contribute in varying degrees in causing obesity.
Given the complexity of obesity, there are many approaches to its treatment. At the most basic level, treatment involves the manipulation of energy intake and energy expenditure. To lose weight one has to take in fewer calories than one expends. To attain this objective, diets limiting the intake of calories are typically coupled with exercise to increase energy expenditure and thus create negative energy balance. Along with this, however, when restricting calories one must be aware of the nutritional needs of the body. Healthy weight loss is best achieved when nutritional requirements of the body are fulfilled during the process of limiting caloric intake.
Since many individuals suffering from obesity also are afflicted with comorbid medical conditions, the determination of appropriate nutritional intake, caloric restriction and exercise regimens should take into account these conditions and, often, the medications associated with them. Safety is of utmost concern when establishing an exercise regimen and in determining nutritional requirements making up a dietary protocol. For example, an appropriate dietary protocol and exercise regimen for weight loss for a 60 year old morbidly obese male individual with hypertension, coronary artery disease and history of heart attack would be very different than the appropriate protocol for a 38 year old moderately obese female having type II diabetes treated with oral medications. Given these factors, it is recommended that protocols for weight loss including nutritional guidelines and exercise be constructed by healthcare professionals including physicians, nutritionists and others.
In this country, there is significant variation in the approaches available to address obesity. Many commercial programs exist, such as Weight Watchers, that provide nutritional and exercise direction along with help to keep on track. There are many individual health care professionals that provide specific weight management services such as nutritionists, trainers, exercise physiologists, counselors, psychologists, nurses and physicians. In some areas, there are more comprehensive programs available at multidisciplinary medical weight management centers where medical management, nutrition, exercise and psychological intervention are provided in a global, coordinated approach. Also, there are surgical approaches available offering a number of procedures aimed at altering caloric intake and absorption.
In addition to services and programs, there are a myriad of weight loss products available. FDA approved prescription medications, herbal products and over the counter products to stimulate metabolism and to increase satiety, prepackaged, low and zero calorie foods and beverages and many other products are available to alter caloric intake. Exercise machines, devices and videos are also available to encourage increased energy expenditure.
In the end, the success of individuals, whether it be in losing weight and maintaining the weight loss or any health enhancement endeavor is most affected by their ability to make positive behavior changes and to maintain those positive behaviors indefinitely.
Well known programs, such as Weight Watchers, have employed weight-loss monitoring data processing systems that have been helpful to participants in this program. In recent years, weight-loss applications have become available for use with iPhones and iPads to assist dieters in successfully meeting their weight loss goals.
While existing weight-loss computing systems have a variety of useful features, such systems are typically cumbersome to use due in part to the complexities of adequate data entry. The difficulties in various data entry steps in such systems are likely to discourage consistent use over a long period of time for many users.
Moreover, there is a need for a diet, exercise and behavioral monitoring system that provides the user with a structured system for addressing the old adage “you are what you eat” in part by providing feedback in real time to the user as to food consumed, exercise performed and/or progress towards goal achievement. In illustrative implementations, such feedback includes nutritional and/or health information about food items to be consumed of which the user may be unaware. Armed with such information, the user is then equipped to make an informed decision whether to eat a selected food item. With such a system, even those who are not overweight (or suffering from any known illness) but who wish to structure a diet that minimizes their odds of in the future suffering from a variety of diseases linked to poor diet, have an opportunity to do so. Still others, who are not overweight but who suffer from high blood pressure, diabetes, lipid disorders, renal disease and perhaps various cancers, have an opportunity to meet their food consumption and exercise goals to take advantage of a diet and exercise protocol that has been linked to helping control such medical conditions. Also individuals in good health who may have very specific health and fitness goals such as bodybuilders, runners, martial arts enthusiasts and others may utilize such a system to help attain their fitness and health goals by monitoring and tracking exercise, behavioral and nutrition parameters.
There is a need for an easy to use weight, nutrition, exercise and behavior monitoring data processing system that, for example, simplifies data entry for food consumed and/or exercise modes of operation and/or behavior parameters, while providing valuable health beneficial feedback and rewards for behavior change and goal achievement. Former smokers and those who are attempting to quit smoking have a dire need to eat in a nutritionally sound manner, exercise as much as they are able, and be rewarded for their efforts to stop smoking. Moreover, it is desirable for such a system to, for example, dynamically adjust to changing user food intake, exercise regimens and behaviors, to change user profiles and associated goals, and to appropriately generate medical warnings as needed.
In practical effect, in illustrative implementations, the mobile computing device executing the weight, nutrition, health, behavior and exercise application software as described herein serves as a simulated personal trainer, dietician/nutritionist, and physician's assistant for the user while having access to massive amounts of personalized health, nutrition and exercise information. In non-limiting, illustrative implementations, a mobile computing device, such as an Iphone, is augmented with a unique weight, nutrition, health, behavior and exercise tracking application and databases that provide enhanced user feedback features and automated data entry.
The illustrative implementations advantageously contribute to the ability of users to maintain positive diet, nutrition and exercise lifestyle changes by monitoring, tracking and adjusting caloric intake, energy expenditure, nutritional information and environmental and behavioral factors. Identifying behavioral issues and working to improve them through prompts and recommendations are used to enhance and maintain positive behavior change. In maintaining the positive behaviors, weight loss and health improvement can be achieved and maintained long term, resulting in significant improvement in quality of life, self esteem, medical conditions and overall health.
In an illustrative implementation (or set of illustrative implementations), the mobile computing device receives food consumption, exercise-related, behavior and other input from various input devices/mechanisms using speech input and digital imaging technology to ease the data entry burden on users and to promote continued long-term usage. In certain illustrative implementations, the system is designed to reward user goal achievement in an automatic, seamless manner, through for example downloading music, books, or other media to the user's mobile computing device via the Internet.
As used herein, it should be understood that any feature identified as being used in one illustrative implementation, is contemplated as being usable in any other illustrative implementation identified herein. Thus, merely because a feature is not expressly identified as being used in a particular illustrative implementation should not be interpreted as an indication that it is not contemplated for use in that implementation. Similarly, any reference herein to “in an implementation/embodiment” or the like should be interpreted as indicating a contemplation of use in any desired implementation. Further, reference to a feature or a set of features being used in “illustrative implementations” should not be construed as an indication that some or all of such features must be used in “all” implementations.
In an illustrative implementation, food consumption and exercise and other goals are set using input from a physician, and/or a nutritionist, and/or healthcare provider, and/or personal trainer, and/or the user, and/or another source. For example, a physician may provide input to set appropriate thresholds for the user including average calorie intake per day, grams of sugar intake per day, amount of exercise per day, etc.
In an illustrative implementation, a “select mode” display is generated. In such an illustrative implementation a wide array of mode select icons are displayed to indicate, for example, a user profile mode for creating a user profile that is modifiable and displayable, a diet selection mode, a food data entry mode, an exercise data entry mode including those using the computing device's GPS functionality, a food purchase mode, a diet and exercise issue mode for addressing a range of issues including user “behavioral” issues in comporting with a diet and exercise program, and various other modes.
One of various mechanisms used by the illustrative implementations to assist, motivate and encourage users to make good, healthy food and exercise choices is a color code system to identify good choices, bad choices and those in between. For example, in an illustrative implementation, the colors GREEN, LIME, YELLOW, ORANGE, and RED, respectively indicate relative values such as Best, Good, Okay, Bad, and Worst with respect to food and exercise choices.
In an illustrative implementation, for each food and exercise activity supported by the system described herein, the system advantageously provides color code feedback to the user with respect to (WRT) any and all of the many nutritional parameters monitored by the system while taking into consideration related health information from a user's profile.
In an illustrative implementation, for each food and each exercise identified by the user, a color code is displayed to the user and dynamically adjusted taking into account, for example, user weight, height, sex, age, health, goals, progress, etc. Such a color code system aids in motivating the user to abide by color codes that are internationally-recognized signals (e.g., “G0” on Green, “Stop” on Red) to select the foods or exercises that provide the greatest benefit (as indicated by the color Green in this example), to avoid the poor choices that provide the least benefit or may even be harmful (as indicated by the color Red in this example), and to advance the color up from Red to Green as soon as possible.
The color coding system used in illustrative implementations is dynamically tailored to individual users in real time. In an illustrative implementation, in generating color code feedback to the user for use in the user's profile generation, the system adjusts the color coding taking into consideration the specific health characteristic to which the user (or the user's physician, nutritionist, or personal trainer) is seeking to improve. For example, in an overweight male user trying to lose weight, fruit is color coded Green but in the overweight female diabetic user who is trying to lose weight and improve her diabetes control, fruit is color coded Orange. Under a variety of circumstances, the same food may undergo a color change for the same user. For example, with the diabetic user, after surpassing a certain amount of fruit in a day, fruit becomes Red due to the sugars in fruit making them not as good for diabetics.
In illustrative implementations with respect to exercise, for a user with significant arthritis in the knees and hips who is trying to lose weight, treadmill walking is coded Red while elliptical machine exercise is coded Orange. However, for such a user, walking or swimming in a pool is coded Green.
In an illustrative implementation, exercise duration times are also factored in by color coding the activity based on the activity itself and the time participating in the activity. In such implementations, too little or too much exercise time generate a less desirable color code, taking into consideration the user's health parameters (heart disease, arthritis, asthma, etc) and the user's goal (to lose/gain weight, improve strength, increase endurance, quit smoking, etc).
In practical effect, the system guides the user to make healthy choices based upon nutrition and health factors tailored to the user, which the user may be unaware of or otherwise avoiding.
In an illustrative implementation, a wide variety of modes may be entered from a “Select Mode” display screen. Initially, a user profile-related mode is entered to permit a user to create, modify, or display his or her user's profile. Entry into such a mode may, for example, enable the user to immediately access his/her current weight loss, calories consumed, calories burned, and other exercise or health-related data to get real-time feedback on his/her progress to date.
In an illustrative implementation, a diet selection mode permits a user to select a diet to be associated with the user's profile that may be used to target one or more medical conditions of the user. In an exemplary implementation, upon the selection of the “diet selection” mode, an array of icons are displayed identifying various diet regimens, at least some of which are targeted to address weight loss, one or more serious medical concerns, and/or other specialized dietary needs such as those of athletes. For example, one or more icons zone in on a diet tailored to addressing the needs of diabetics, cancer patients, gluten-intolerant individuals, individuals with high blood pressure, or individuals with other major medical conditions, who are attempting to stop smoking or drinking, etc. In an illustrative implementation, the application generates selection of a diet by accessing an associated database that contains pre-formulated breakfasts, lunches and dinners targeted to comport with the selected diet and associates such meals with the user's profile.
In an illustrative implementation, one of such icons available in the diet selection mode would, for example, enable selection of the “GOMBS” diet (or a variation thereof) promoted in the mass media by Dr. Joel Fuhrman. In such an implementation, variations of meals following the spirit of the GOMBS diet as identified in Dr. Fuhrman's book “Secrets to Healthy Cooking” are stored in one of the databases used in the illustrative implementation. GOMBS is an acronym for Greens, Onions, Mushrooms, Beans & berries, and Seeds & nuts. Such foods have reportedly been associated with healthier blood vessels/blood flow, enhanced weight loss, reduced suffering from certain cancers, anti-diabetic and other beneficial properties.
In an illustrative implementation, entry into a food consumption data entry mode (Food mode) permits the user to enter into the system, food that is consumed either in or outside a user's home in a manner that is as user-friendly as possible. Over a period of time, users tend to eat one or more of the same favorite meals for breakfast, lunch, or dinner on a consistent basis. Taking advantage of this habituated tendency, the system can learn a great deal about the user's present nutrition profile by initially asking him/her to declare his/her Top 5 favorite meals. In an illustrative implementation where the food is nutritional and low in calories, a user works with, for example, a physician/nutritionist/other consultant to select various breakfast, lunch, and dinner combinations that have beneficial amounts of nutrition (e.g., low in calories, sugars, saturated fats, sodium, etc.) that are then stored in the user's profile (or a database associated therewith). For example, a user who has chosen to eat a breakfast of Cheerios, with raspberries, blueberries, and skim milk may have an associated user profile having such a breakfast identified as “breakfast number 1” and storing (or otherwise identifying by pointing to a database storage location) a wide array of nutritional information for such a breakfast including, for example, calories and sugar content. In such an implementation, using speech recognition software, the system recognizes, for example, the user stating “breakfast number 1” in response to a verbal or displayed prompt to describe the breakfast to be consumed. In certain other illustrative implementations, a touch screen display (or other identification) of a particular food may be used to obtain user confirmation that the speech recognition software accurately decoded the food he/she identified.
After speech recognition software determines, for example, that the user has stated the particular food consumed and the food amount, the system then determines the caloric, nutritional, and other health-related characteristics of the food consumed which is stored and analyzed as described herein. In the above example, a Green color code is displayed to the user consuming such a breakfast number 1. Additionally, in certain illustrative implementations, image processing technology may be utilized to identify the food and the caloric and other nutritional/health-related characteristics of the food consumed. This same user/system interactive process is likewise used for the user to store and later specify other favorite meals such as “Lunch number 3”, “Dinner number 5”, etc.
In an illustrative implementation, a user's exercise activities are tracked and analyzed. In one of various exercise modes, GPS technology embodied in the user's computing device is used to automatically acquire user coordinate position data using the GPS receiver associated with the mobile computing device, and the system monitors the time over which running, walking, or bicycling exercise activities have occurred. After user entry of the type of exercise being undertaken and after determining the distance traveled during the monitored time, the system generates an estimate of the number of calories burned by the user during such GPS-tracked activity.
In an illustrative embodiment, other exercise modes may be entered in which, for example, speech analysis software is utilized to enable the user to input a specific type of exercise: for example, various exercise-related “tags” are stored in a newly-created exercise record identifying the duration, resistance, rest interval, and other characteristics of the exercise. Under circumstances where various conventional health club exercise machines are used, the system stores the generated output of such exercise machines, such as elliptical machines, stationary bicycle machines, stepper machines, etc., that generate, for example, the number of calories burned during an exercise session.
Further, in other illustrative implementations, a food purchasing mode may be entered to guide the user during food shopping or at a restaurant to determine whether a food product being purchased is consonant with the user's profile and associated goals and health issues. In an illustrative implementation, a database is accessed to identify, where possible, alternative foods of the same food type to enable a user, for example, to select a desired food and yet cut down on, for example, the amount of sugars, fats, sodium, or calories consumed.
Further, in another illustrative example, a diet/exercise issue mode may be entered where the user selects a category corresponding with a behavioral issue that may be impacting diet or exercise success. The user is then prompted to answer questions regarding the behavioral issue raised by the user's problem. The responses are analyzed by the system and the system provides the user with recommendations to improve the behavior: e.g., to eat an apple at 3 PM in response to a user query regarding hunger issues in the middle of the afternoon.
Additionally, in illustrative implementations access to external servers and databases is advantageously utilized to provide a behavior enhancing reward system designed to motivate users to achieve their goals through rewards based on goal achievement and/or progress towards goal achievement. In an illustrative implementation, any diet, exercise, health or nutritional goal being met may trigger an award generation, including weight-related goals, exercise-related goals and smoking cessation-related goals. A reward may be embodied in a wide variety of forms including, without limitation, automatically downloaded music, movies, digital versions of TV shows, music videos, cash, discounts at movies, restaurants (particularly those that include a wide range of healthy alternatives), discounts at sporting events, mobile games, mobile gaming currency, other mobile applications, etc. In an illustrative implementation, a user's types of reward preferences, e.g., music, electronic book, etc., are stored in the user's profile to guide the system in generating and downloading an appropriate reward.
These and other features of the illustrative implementations will become apparent from a review of the drawings of which: